What can deep learning do for applications today? How should I think about using deep learning for my problem? If I want to apply deep learning in a new way, how do I get started? In this talk, Bryan will share some characteristics of successful deep learning applications, and some things to think about when starting a new deep learning application.
Speech is the user interface of the future, but today's implementations often fail when we need them the most, such as in noisy environments or when the microphone isn't close at hand. At Baidu, an increasing fraction of our users employ speech interfaces to find what they are looking for. In this talk, I will show how next generation deep learning models can provide state-of-the-art speech recognition performance. We train these models using clusters of GPUs using CUDA, MPI and Infiniband.
Copperhead is a data parallel language suitable for GPU programming, embedded in Python, which aims to provide both a productive programming environment as well as excellent computational efficiency. Copperhead programs are written in a small, restricted subset of the Python language, using standard constructs like map and reduce, along with traditional data parallel primitives like scan and sort. Copperhead programs interoperate with existing Python numerical and visualization libraries such as NumPy, SciPy, and Matplotlib. In this talk, we will discuss the Copperhead language, the open-source Copperhead runtime, and selected example programs.